We have shown that non-parametric linkage methods can be powerful tools for screening for linkage for susceptibility genes for complex, quantitative traits. Using these methods in simulated data from the Genetic Analyis Workshop 9, we were able to identify a locus accounting for 8% of the variance of a trait. We have shown that the power of the affected-sib-pair (ASP) test can be improved by carrying out a multipoint test. For example, the p-value of ASP sharing for Bipolar illness on one chromosomal segment on chromosome 18 is = 0.00008. We have extended the transmission disequilibrium test (TDT) to marker loci with multiple alleles and have applied this test to test for association of markers on chromosome 18 to bipolar illness. We have demonstrated a possible association of the locus D18S53 to the disease (p < 0.05), with one allele identified as being transmitted less often than expected by chance. We are examining new methods to improve the power of linkage detection. We have shown that if a whole genome is screened for linkage to a trait, a region around a disease locus has increased haplotype sharing in pairs of affected relatives. When increased haplotype sharing occurs by chance at one location (i.e. no disease locus is present), the area around this location does not have the degree of increased sharing as in the case of a true disease locus. This difference can be used to develop a more powerful statistic for linkage detection.